Course Outline
Introduction to Applied Machine Learning
- Distinguishing between statistical learning and Machine Learning
- Cycles of iteration and evaluation
- Managing the Bias-Variance trade-off
Supervised Learning and Unsupervised Learning
- Overview of Machine Learning languages, types, and use cases
- Comparing Supervised vs. Unsupervised Learning paradigms
Supervised Learning
- Implementing Decision Trees
- Utilizing Random Forests
- Techniques for Model Evaluation
Machine Learning with Python
- Selecting appropriate libraries
- Integrating add-on tools
Regression
- Fundamentals of Linear regression
- Handling generalizations and Nonlinearity
- Practical Exercises
Classification
- Refresher on Bayesian principles
- Application of Naive Bayes
- Implementation of Logistic regression
- Using K-Nearest neighbors
- Practical Exercises
Cross-validation and Resampling
- Exploring Cross-validation approaches
- Applying the Bootstrap method
- Practical Exercises
Unsupervised Learning
- Performing K-means clustering
- Reviewing representative examples
- Addressing challenges in unsupervised learning beyond K-means
Neural networks
- Understanding Layers and nodes
- Exploring Python neural network libraries
- Working with scikit-learn
- Working with PyBrain
- Introduction to Deep Learning
Requirements
A solid working knowledge of the Python programming language is required. Additionally, a foundational understanding of statistics and linear algebra is recommended.
Testimonials (7)
Interesting knowledge
Gabriel - MINDEF
Course - Machine Learning with Python – 4 Days
The trainer was a practitioner with a lot of experience and had a very good knowledge of the material.
Witold Iwaniec - City of Calgary
Course - Machine Learning with Python – 4 Days
The trainer because he could handle almost every subject and situation.
Florin Babes - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
The manner in which the trainer explained the concepts, his positive and welcoming attitude and the real-world examples provided for each exercise.
Ovidiu Calita - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
Very good training session with nice documentation and exercises and Kristian did it like a professional he is.
Adrian Boulescu - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
I like that he is very skilled and has lots of knowledge in his domain.
dan dumitriu - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
rich documentation and many resources as course support, as well as resources for the post-course learning process
